Authors:H. Khoshro, M. Bihamta, M. Hassanii, M. Omidi, and M. Aghaei
., Simeone, M., Masci, S., Porceddu, E. 1997. Molecular characterization of a LMW-GS gene located on chromosome 1B an the development of primers specific for the
complex locus in durumwheat. Theor. Appl. Genet.
Authors:A. Etminan, A. Pour-Aboughadareh, R. Mohammadi, L. Shooshtari, M. Yousefiazarkhanian, and H. Moradkhani
In the present study, efficiency of the artificial neural network (ANN) method to identify the best drought tolerance indices was investigated. For this purpose, 25 durum genotypes were evaluated under rainfed and supplemental irrigation environments during two consecutive cropping seasons (2011–2013). The results of combined analysis of variance (ANOVA) revealed that year, environment, genotype and their interaction effects were significant for grain yield. Mean grain yield of the genotypes ranged from 184.93 g plot–1 under rainfed environment to 659.32 g plot–1 under irrigated environment. Based on the ANN results, yield stability index (YSI), harmonic mean (HM) and stress susceptible index (SSI) were identified as the best indices to predict drought-tolerant genotypes. However, mean productivity (MP) followed by geometric mean productivity (GMP) and HM were found to be accurate indices for screening drought tolerant genotypes. In general, our results indicated that genotypes G9, G12, G21, G23 and G24 were identified as more desirable genotypes for cultivation in drought-prone environments. Importantly, these results could provide an evidence that ANN method can play an important role in the selection of drought tolerant genotypes and also could be useful in other biological contexts.
Authors:K. Balla, M. Rakszegi, S. Bencze, I. Karsai, and O. Veisz
., Ciaffi, M., Lafiandra, D., Borghi, B. (1997): Effect of the duration and intensity of heat shock during grain filling on dry matter and protein accumulation, technological quality and protein composition in bread and durumwheat. Aust. J. Plant Physiol
Authors:V. Oslovičová, J.R. Simmonds, J.W. Snape, Z. Gálová, Z. Balážová, and I. Matušíková
In this study we evaluate the genetic diversity of a selection of wheat accessions characteristically grown and adapted to mid-European environments, using various molecular marker systems. Thirty-three simple sequence repeat (SSR) markers were used alongside genic markers for known dwarfing genes, flowering time genes, and grain hardness genes, namely Rht-B1, Rht-D1, Ppd-D1, Vrn-A1, Vrn-B1, Vrn-D1 and Pinb-D1. In addition, variation was scored for the high-molecular-weight glutenin storage proteins, responsible for dough technological quality. A dendrogram was constructed using the UPGMA algorithm, based on the molecular data and the country of origin, giving an overview of their genetic similarity and relationships. The potential for the use of some agronomic traits in breeding, by providing a basis for multi-trait genetic selection in wheat breeding programs is discussed. Estimating the breeding values of crops using multiple genetic markers might help in breeding for varieties with good technological quality for growing under desired climatic conditions.